Modeling Ecological Success of Common Pool Resource Systems Using Large Datasets

The influence of many factors on ecological success in common pool resource management is still unclear. This may be due to methodological issues. These include causal complexity, a lack of large-N-studies, and non-linear relationships between factors. We address all three issues with a new methodological approach, artificial neural networks, which is discussed in detail. It allows us to develop a model with comparably high predictive power. In addition, two success factors are analyzed: legal security and institutional fairness. Both factors show a positive impact on success in irrigation and fisheries supporting the view that there are sector-independent success factors.